Nowadays, intelligent packaging has become very popular. It can quickly detect problems that arise during food production or circulation by monitoring the quality and safety of food. Anthocyanins have attracted widespread attention as a material for manufacturing smart food packaging, as they are sensitive to changes in pH, and small changes in pH can cause changes in the color of anthocyanins. The incorporation of anthocyanins often causes different changes in the properties of the films. The effects of anthocyanins on different properties of the films, including barrier, stability, mechanical properties, antioxidant, antibacterial and pH-sensitive were reviewed. We suggest that anthocyanins have the potential to extend the shelf life and monitor the food’s freshness and quality in intelligent packaging.

This study aims to determine the differences in the effects of vacuum packaging and modified atmosphere packaging on the quality, flavor, and microorganisms of Mianning ham. Vacuum packaging exhibits stronger antioxidant properties (a* value), while modified atmosphere packaging inhibits microorganisms and delays the decline of Aw through CO₂. A total of 249 volatile substances was determined in the ham, while 19 main flavor substances, such as 1-octanol, hexanal, 2-nonanone, and p-cresol, were identified. It was found that the packaging method significantly affected the contents of alcohols and hydrocarbons. At the phylum level, Firmicutes is the dominant bacterial community. At the genus level, in the vacuum packaging group, Tetragenococcus and Carnobacterium are the core contributing bacteria for flavor, while Staphylococcus is dominant in both packaging types and may inhibit flavor formation.

The continuous advancement of non-destructive testing technology has led to a surge in research on the application of hyperspectral imaging (HSI) technology within the meat products industry. HSI is capable of precisely identifying physical and chemical indicators such as salt, moisture, protein, and fat in dry-cured ham, including the coefficient of determination for salt content and the prediction error of water activity. It also evaluates sensory indicators like viscosity, color, and marbling, including the visualization and classification accuracy of marble patterns. Additionally, it can identify surface mold species with a sensitivity of 85% and a specificity of 86% for distinguishing ochratoxin A-producing bacteria from non-producing bacteria. The unique advantage of HSI which ‘fuses spectral and spatial information’ has enabled the development of various data processing models, such as partial least squares regression and support vector machine-discriminant analysis. These models allow for the simultaneous detection of multiple indicators and the visualization of component spatial distribution, offering an intuitive basis for quality control. This paper summarizes the progress of HSI technology in the quality inspection of dry-cured ham, analyzes its potential for industrial online inspection, including issues such as fat interference, and provides a foundation for future quality identification, optimization, and standardization of dry-cured ham.